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Python for data analysis

Author: Wes McKinney
Publisher: Sebastopol, CA : O'Reilly Media, [2013] ©2013
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
"Python for Data Analysis is concerned with the nuts and bolts of manipulating, processing, cleaning, and crunching data in Python. It is also a practical, modern introduction to scientific computing in Python, tailored for data-intensive applications. This is a book about the parts of the Python language and libraries you'll need to effectively solve a broad set of data analysis problems. This book is not an  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
McKinney, Wes.
Python for data analysis.
(DLC) 2012538094
(OCoLC)794362690
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Wes McKinney
ISBN: 9781449323615 1449323618 9781449323622 1449323626
OCLC Number: 809537079
Notes: Includes index.
Description: 1 online resource (xiii, 452 pages) : illustrations
Contents: Preliminaries --
Introductory examples --
IPython : an interactive computing and development environment --
NumPy basics : arrays and vectorized computation --
Getting started with pandas --
Data loading, storage, and file formats --
Data wrangling : clean, transform, merge, reshape --
Plotting and visualization --
Data aggregation and group operations --
Time series --
Financial and economic data applications --
Advanced NumPy --
Appendix: Python language essentials.
Responsibility: Wes McKinney.

Abstract:

"Python for Data Analysis is concerned with the nuts and bolts of manipulating, processing, cleaning, and crunching data in Python. It is also a practical, modern introduction to scientific computing in Python, tailored for data-intensive applications. This is a book about the parts of the Python language and libraries you'll need to effectively solve a broad set of data analysis problems. This book is not an exposition on analytical methods using Python as the implementation language. Written by Wes McKinney, the main author of the pandas library, this hands-on book is packed with practical cases studies. It's ideal for analysts new to Python and for Python programmers new to scientific computing. Use the IPython interactive shell as your primary development environment ; Learn basic and advanced NumPy (Numerical Python) features ; Get started with data analysis tools in the pandas library ; Use high-performance tools to load, clean, transform, merge, and reshape data ; Create scatter plots and static or interactive visualizations with matplotlib ; Apply the pandas groupby facility to slice, dice, and summarize datasets ; Measure data by points in time, whether it's specific instances, fixed periods, or intervals ; Learn how to solve problems in web analytics, social sciences, finance, and economics, through detailed examples"--Provided by publisher.

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